Statistics of switching-time jitter for a tunnel diode threshold-crossing detector

Statistics of switching time jitter for tunnel diode threshold crossing detecto

Developmental design, fabrication, and test of acoustic suppressors for fans of high bypass turbofan engines

An analysis procedure was developed for design of acoustically treated nacelles for high bypass turbofan engines. The plan was applied to the conceptual design of a nacelle for the quiet engine typical of a 707/DC-8 airplane installation. The resultant design was modified to a test nacelle design for the NASA Lewis quiet fan. The acoustic design goal was a 10 db reduction in effective perceived fan noise levels during takoff and approach. Detailed nacelle designs were subsequently developed for both the quiet engine and the quiet fan. The acoustic design goal for each nacelle was 15 db reductions in perceived fan noise levels from the inlet and fan duct. Acoustically treated nacelles were fabricated for the quiet engine and quiet fan for testing. Performance of selected inlet and fan duct lining configurations was experimentally evaluated in a flow duct. Results of the tests show that the linings perform as designed

Statistical Communication Theory

Contains reports on work completed and one research projects.Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DA 28-043-AMC-02536(E)National Aeronautics and Space Administration (Grant NGR-22-009-304

NEW TOOLS FOR NEW TIMES

The purpose of this presentation is to challenge statisticians to develop new tools needed by modern scientists. We are in the midst of a Scientific Revolution being driven by computers and the internet. Scientists are gathering huge amounts of data on the usual measurements while continually developing new instruments for new measurements. Data sets full of measurements which may pertain to the scientist\u27s research are easily available on the internet. Scientists are being overwhelmed with data. Agricultural producers and consumers are asking for more information. Scientists need new tools to evaluate variation. They need help with sampling - numbers of observations required and proper sampling schemes. Examples and suggestions will be offered. Statistical Process Control as applied to farming systems will be discussed

A new index to measure positive dependence in trivariate distributions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)We introduce a new index to detect dependence in trivariate distributions. The index is based on the maximization of the coefficients of directional dependence over the set of directions. We show how to calculate the index using the three pairwise Spearman's rho coefficients and the three common 3-dimensional versions of Spearman's rho. We obtain the asymptotic distributions of the empirical processes related to the estimators of the coefficients of directional dependence and also we derive the asymptotic distribution of our index. We display examples where the index identifies dependence undetected by the aforementioned 3-dimensional versions of Spearman's rho. The value of the new index and the direction in which the maximal dependence occurs are easily computed and we illustrate with a simulation study and a real data set. (C) 2012 Elsevier Inc. All'rights reserved.We introduce a new index to detect dependence in trivariate distributions. The index is based on the maximization of the coefficients of directional dependence over the set of directions. We show how to calculate the index using the three pairwise Spearma115481495FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP [10/51940-5]CNPq [485999/2007-2, 476501/2009-1]10/51940-5485999/2007-2; 476501/2009-

Statistical Communication Theory

Contains reports on work completed and one research projects.Joint Services Electronics Programs (U. S. Army, U.S. Navy, and U.S. Air Force) under Contract DA 28-043-AMC-02536(E)National Aeronautics and Space Administration (Grant NsG-496

The structure of the class of maximum tsallis-havrda-chavat entropy copulas

A maximum entropy copula is the copula associated with the joint distribution, with prescribed marginal distributions on [0, 1], which maximizes the Tsallis-Havrda-Chavat entropy with q = 2. We find necessary and sufficient conditions for each maximum entropy copula to be a copula in the class introduced in Rodriguez-Lallena and Ubeda-Flores (2004), and we also show that each copula in that class is a maximum entropy copula.A maximum entropy copula is the copula associated with the joint distribution, with prescribed marginal distributions on [0, 1], which maximizes the Tsallis-Havrda-Chavat entropy with q = 2. We find necessary and sufficient conditions for each maximum entropy copula to be a copula in the class introduced in Rodriguez-Lallena and Ubeda-Flores (2004), and we also show that each copula in that class is a maximum entropy copula.18

Bayesian Variable Selection for Non-Gaussian Responses: A Marginally Calibrated Copula Approach

We propose a new highly flexible and tractable Bayesian approach to undertake variable selection in non-Gaussian regression models. It uses a copula decomposition for the joint distribution of observations on the dependent variable. This allows the marginal distribution of the dependent variable to be calibrated accurately using a nonparametric or other estimator. The family of copulas employed are `implicit copulas' that are constructed from existing hierarchical Bayesian models widely used for variable selection, and we establish some of their properties. Even though the copulas are high-dimensional, they can be estimated efficiently and quickly using Markov chain Monte Carlo (MCMC). A simulation study shows that when the responses are non-Gaussian the approach selects variables more accurately than contemporary benchmarks. A real data example in the Web Appendix illustrates that accounting for even mild deviations from normality can lead to a substantial increase in accuracy. To illustrate the full potential of our approach we extend it to spatial variable selection for fMRI. Using real data, we show our method allows for voxel-specific marginal calibration of the magnetic resonance signal at over 6,000 voxels, leading to an increase in the quality of the activation maps

Statistical Communication Theory

Contains reports on two research projects.National Science Foundation (Grant GP-2495)National Institutes of Health (Grant MH-04737-04),National Aeronautics and Space Administration (Grant NsG-496